During the last years, interest on hybrid metaheuristics has risen considerably in the field of optimization and machine learning. The best results found for many optimization problems in science and industry are obta...
详细信息
During the last years, interest on hybrid metaheuristics has risen considerably in the field of optimization and machine learning. The best results found for many optimization problems in science and industry are obtained by hybrid optimization algorithms. Combinations of optimization tools such as metaheuristics, mathematical programming, constraint programming and machine learning, have provided very efficient optimization algorithms. Four different types of combinations are considered in this paper: (i) Combining metaheuristics with complementary metaheuristics. (ii) Combining metaheuristics with exact methods from mathematical programming approaches which are mostly used in the operations research community. (iii) Combining metaheuristics with constraint programming approaches developed in the artificial intelligence community. (iv) Combining metaheuristics with machine learning and data mining techniques.
Most studies of inventory consolidation effects assume time-independent random demand. In this article, we consider time-dependence by incorporating an autoregressive moving average structure to model the demand for p...
详细信息
Most studies of inventory consolidation effects assume time-independent random demand. In this article, we consider time-dependence by incorporating an autoregressive moving average structure to model the demand for products. With this modeling approach, we analyze the effect of consolidation on inventory costs compared to a system without consolidation. We formulate an inventory setting based on continuous-review using allocation rules for regular transshipment and centralization, which establishes temporal structures of demand. Numerical simulations demonstrate that, under time-dependence, the demand conditional variance, based on past data, is less than the marginal variance. This finding favors dedicated locations for inventory replenishment. Additionally, temporal structures reduce the costs of maintaining safety stocks through regular transshipments when such temporal patterns exist. The obtained results are illustrated with an example using real-world data. Our investigation provides information for managing supply chains in the presence of time-patterned demands that can be of interest to decision-makers in the supply chain.
The last decade has witnessed a burgeoning interest in transportation electrification from the academia, government, and industry. A current barrier faced by fleet operators is the charge scheduling, a problem that be...
详细信息
The last decade has witnessed a burgeoning interest in transportation electrification from the academia, government, and industry. A current barrier faced by fleet operators is the charge scheduling, a problem that becomes more pronounced with the fleet size, heterogeneity (in both the vehicle fleet and the charging infrastructure), and uncertainty, which has given rise to the Charging-as-a-Service (CaaS) industry. A CaaS provider intermediates between the fleet owner and the macrogrid, and is key to ease the transition to the future of transportation with electric vehicles. This paper addresses the CaaS providers' electric vehicle fleet (EVF) charge scheduling problem with time-varying electricity prices. We develop a rolling-horizon online optimization approach reinforced with a predictive model and a heuristic warm-start to solve this emerging multi-stage stochastic optimization problem. A numerical experiment demonstrates that our method outperforms an industry benchmark by 13.24%-18.44% with respect to charging costs under the tested conditions. In addition to cost savings, the energy use profile of resulting schedules consumes less energy in peak hours, which can reduce carbon emissions and improve grid stability. Thus, the proposed approach identifies charging schedules that simultaneously benefit CaaS providers, fleet owners, electric power producers, and the macrogrid in general.
This paper aims to model maintenance planning with a dynamic opportunistic approach for a job-shop pro-duction system. One issue in such a system is the positive or negative economic dependency. That is grouping maint...
详细信息
This paper aims to model maintenance planning with a dynamic opportunistic approach for a job-shop pro-duction system. One issue in such a system is the positive or negative economic dependency. That is grouping maintenance activities may decrease or increase system costs. Furthermore, many maintenance models consider the planning of maintenance only based on a long-term horizon. While short-term and real circumstances such as system characteristics and constraints, workload, number of available maintenance teams, and variable main-tenance cost and time are almost ignored. To address these issues, a rolling-horizon approach based on a long-term maintenance plan is proposed so that subsequent scheduling of maintenance and production activities are performed as events unfold through the time. Hence, we have developed a mixed-integer nonlinear mathematical model to simultaneously make decisions on maintenance selection, maintenance grouping, lot sizing and pro-duction scheduling. The objective function includes the costs of preventive and corrective maintenance activities as well as various production costs such as production and setup, tardiness penalty, and safety stock penalty. A self-adaptive Cuckoo Optimization Algorithm has been used to solve the proposed model. Numerical experiments were conducted to demonstrate the validity of the model and investigate the efficiency and effectiveness of the optimization algorithm.
In this paper, we establish a strong convergence theorem for hierarchical problems, an equivalent relation between a multiple sets split feasibility problem and a fixed point problem. As applications of our results, w...
详细信息
In this paper, we establish a strong convergence theorem for hierarchical problems, an equivalent relation between a multiple sets split feasibility problem and a fixed point problem. As applications of our results, we study the solution of mathematical programming with fixed point and multiple sets split feasibility constraints, mathematical programming with fixed point and multiple sets split equilibrium constraints, mathematical programming with fixed point and split feasibility constraints, mathematical programming with fixed point and split equilibrium constraints, minimum solution of fixed point and multiple sets split feasibility problems, minimum norm solution of fixed point and multiple sets split equilibrium problems, quadratic function programming with fixed point and multiple set split feasibility constraints, mathematical programming with fixed point and multiple set split feasibility inclusions constraints, mathematical programming with fixed point and split minimax constraints.
Energy integration and mass integration are important approaches to achieve energy saving and emission reduction in the process ***,the methods can be classified into two groups,viz.:conceptual design methods and math...
详细信息
Energy integration and mass integration are important approaches to achieve energy saving and emission reduction in the process ***,the methods can be classified into two groups,viz.:conceptual design methods and mathematical programming *** former includes mainly graphical methods based on pinch technology that is operated easily.A feasible solution can be quickly *** design methods are sequential in nature including two steps,namely:targeting and *** latter is based on superstructure optimization,and corresponding algorithm is adopted to solve the *** trade-offs and connections among the entire network can be established and *** factors can be considered and optimized simultaneously by mathematical programming *** paper describes the synthesis of heat integrated water allocation networks(HIWAN)based on both conceptual design methods and mathematical programming methods *** addition,the characteristics and shortcomings of the existing research methods are summarized,and the future research direction is prospected.
Reversible computing is a promising field that explores the possibility of performing computations in such a way that the initial state of the computation can be uniquely reconstructed from its final state. In this wo...
详细信息
This article describes the application of modern algorithms to crack the official encryption method of the Spanish Civil War: the Strip Cipher. It shows the differences in efficiency and effectiveness between a geneti...
详细信息
This article describes the application of modern algorithms to crack the official encryption method of the Spanish Civil War: the Strip Cipher. It shows the differences in efficiency and effectiveness between a genetic algorithm and mathematical programming, the optimisation methods known collectively as mathematical optimisation. Unlike the genetic algorithm, the programming approach has been seen to lead to high computational costs or to non-legible plain texts, which make it impractical. To improve the search for the genetic operators used, a dictionary is applied to identify possible words in each partially decrypted text and, thus, unblock the process. Results and conclusions have been obtained by analysing the outcome of the algorithms when attacking real ciphertexts found in the General Archive of the Spanish Civil War in Spain. Both the mathematical programming and the genetic algorithm approaches have merit, but the latter has considerable practical advantages.
Computing control invariant sets is paramount in many applications. The families of sets commonly used for computations are ellipsoids and polyhedra. However, searching for a control invariant set over the family of e...
详细信息
Computing control invariant sets is paramount in many applications. The families of sets commonly used for computations are ellipsoids and polyhedra. However, searching for a control invariant set over the family of ellipsoids is conservative for systems more complex than unconstrained linear time invariant systems. Moreover, even if the control invariant set may be approximated arbitrarily closely by polyhedra, the complexity of the polyhedra may grow rapidly in certain directions. An attractive generalization of these two families are piecewise semi-ellipsoids. We provide in this letter a convex programming approach for computing control invariant sets of this family.
Timetabling problem needs to be well defined and efficiently handled in order for any type of institution or organization to be well organized and systematic. Developing an effective timetable is a tedious task, espec...
详细信息
Timetabling problem needs to be well defined and efficiently handled in order for any type of institution or organization to be well organized and systematic. Developing an effective timetable is a tedious task, especially when it involves a large organization. mathematical programming is often used in solving the timetabling problem. The purpose of this research is to adapt a model for Malaysian universities course timetabling. In general, we aim to determine the flexibility and compatibility of the model towards generating a timetable for Malaysian universities. The adapted model is applied to a selected university in Malaysia where the constraints are modified according to the university regulations and demands. It is then tested using LINGO and is found to be effective and fulfil the requirements of the university. The timetable fulfils the various requirements made by lecturers and the facilities provided. An effective timetable is generated where the different courses, groups of students and lecturers are well scheduled.
暂无评论